2000/11/09 by Henry D. I. Abarbanel, Henry D.I. Abarbanel, Naoki Masuda +3
Computer Science · Mathematics · Physics and Astronomy · #Blind Source Separation Techniques #Channel (broadcasting) #Chaos control and synchronization #Distribution (mathematics) #Information theory #Mathematical Analysis and Transform Methods #Mutual information #Nonlinear system #Phase space #Series (stratigraphy) #Statistic #Time series #nlin.CD
paper · pdf · doi:10.1016/s0375-9601(01)00128-1
4 pages, 2 figures, RevTeX V4b4, submitted to Phys. Rev. Lett
arxiv created 2000/11/09 · openalex publication_date 2001/04/01 · arxiv updated 2009/11/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/06
In the analysis of time series from nonlinear sources, mutual information (MI) is used as a nonlinear statistical criterion for the selection of an appropriate time delay in time delay reconstruction of the state space. MI is a statistic over the sets of sequences associated with the dynamical source, and we examine here the distribution of MI, thus going beyond the familiar analysis of its average alone. We give for the first time the distribution of MI for a standard, classical communications channel with Gaussian, additive white noise. For time series analysis of a dynamical system, we show how to determine the distribution of MI and discuss the implications for the use of average mutual information (AMI) in selecting time delays in phase space reconstruction.